A Deep Learning Method for Automatic Identification of Drusen and Macular Hole from Optical Coherence Tomography

Stud Health Technol Inform. 2022 May 25:294:565-566. doi: 10.3233/SHTI220525.

Abstract

Deep Learning methods have become dominant in various fields of medical imaging, including ophthalmology. In this preliminary study, we investigated a method based on Convolutional Neural Network for the identification of drusen and macular hole from Optical Coherence Tomography scans with the aim to assist ophthalmologists in diagnosing and assessing retinal diseases.

Keywords: Convolutional Neural Networks; Deep Learning; Drusen; Macular Holes; Optical Coherence Tomography; Retinal diseases.

MeSH terms

  • Deep Learning*
  • Humans
  • Retina
  • Retinal Diseases*
  • Retinal Perforations* / diagnostic imaging
  • Tomography, Optical Coherence / methods